Sensitivity and specificity are measures used to evaluate how well a medical test detects a disease. Sensitivity refers to the percentage of sick people who test positive, while specificity refers to the percentage of healthy people who test negative. In an example evaluating a test on 100 people where 30 had a disease, the test correctly identified 25 sick people and incorrectly identified 5 as healthy, for a sensitivity of 25/30. It correctly identified 68 healthy people and incorrectly identified 2 as sick, for a specificity of 68/70.

1. Sensitivity & Specificity
(Validity)
By Mohammadi M.
Master of Science (Medical Physics)
Department of Medical Physics, KUMS

2. Sensitivity & Specificity (Validity)
 Measure how ‘good’ a test is at detecting
binary features of interest
(disease/no disease)

3. Terms
 True positive: Sick people correctly identified
as sick
 False positive: Healthy people incorrectly
identified as sick
 True negative: Healthy people correctly
identified as healthy
 False negative: Sick people incorrectly
identified as healthy

4. Sensitivity & Specificity
 Sensitivity = P (Test+ | Disease+)
 Specificity = P (Test- | Disease-)

5. Sensitivity & Specificity


8. Example
 There are 100 people with 30 having disease A
 A test designed to identify who has the
disease and who does not
 We want to evaluate how good the test is

9. Sensitivity & Specificity
Disease
+
Disease
-
Total
Test
+
25 2 27
Test
-
5 68 73
Total 30 70 100

10. Sensitivity & Specificity
25/30
sensitivity
68/70
specificity
Disease
+
Disease
-
Total
Test
+
25 2 27
Test
-
5 68 73
Total 30 70 100